Paper summarymarekProposing character-based extensions to a neural MT system for grammatical error correction. OOV words are represented in the encoder and decoder using character-based RNNs. They evaluate on the CoNLL-14 dataset, integrate probabilities from a large language model, and achieve good results.
https://i.imgur.com/r0Bsxp5.png

Proposing character-based extensions to a neural MT system for grammatical error correction. OOV words are represented in the encoder and decoder using character-based RNNs. They evaluate on the CoNLL-14 dataset, integrate probabilities from a large language model, and achieve good results.
https://i.imgur.com/r0Bsxp5.png